ArticleSocial science & medicine (1982)2014
Results from using a new dyadic-dependence model to analyze sociocentric physician networks.
Article in Social science & medicine (1982), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Applications of network analysis to routinely collected health care data: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2018Pooled it
- A Scoping Review of Multilevel Patient-Sharing Network Measures in Health Services Research.Medical care research and review : MCRR · 2025Article
- Article
- Network approaches and interventions in healthcare settings: A systematic scoping review.PloS one · 2023Article
- Review of social networks of professionals in healthcare settings-where are we and what else is needed?Globalization and health · 2021Review
- A scoping review of patient-sharing network studies using administrative data.Translational behavioral medicine · 2018Article
- From social networks to health: Durkheim after the turn of the millennium. Introduction.Social science & medicine (1982) · 2015Article
- Tie Decay and Dissolution: Contentious Prescribing Practices in the Prescription Drug Epidemic.Organization science (Providence, R.I.)Article
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4 authors.
Funding
Abstract
Professional physician networks can potentially influence clinical practices and quality of care. With the current focus on coordinated care, discerning influences of naturally occurring clusters and other forms of dependence among physicians' relationships based on their attributes and care patterns is an important area of research. In this paper, two directed physician networks: a physician influential conversation network (N = 33) and a physician network obtained from patient visit data (N = 135) are analyzed using a new model that accounts for effect modification of the within-dyad effect of reciprocity and inter-dyad effects involving three (or more) actors. The results from this model include more nuanced effects involving reciprocity and triadic dependence than under incumbent models and more flexible control for these effects in the extraction of other network phenomena, including the relationship between similarity of individuals' attributes (e.g., same-gender, same residency location) and tie-status. In both cases we find extensive evidence of clustering and triadic dependence that if not accounted for confounds the effect of reciprocity and attribute homophily. Findings from our analysis suggest alternative conclusions to those from incumbent models.
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